Abstract: Histological staining, interpreted by a pathologist, has remained the gold standard for cancer diagnosis and staging for over 100 years. There is a growing need for better – and more personalized – cancer treatments, to provide oncologists with the tools they need to best treat their patients. The advent of “molecular medicine”, or targeted therapeutic strategies that rely on knowledge of particular mutations in a cancer in order to tailor treatment, has improved cancer therapy for many patients. This has led to the use of companion diagnostics, in which tumor biopsies are stained for a specific marker or set of markers, using immunohistochemical approaches. The information obtained from the degree of staining or spatial arrangement of stained cells within the tumor helps to identify tumor molecular subclasses that may benefit from such tailored therapeutic approaches.

The increase in the number of slides being stained for specific markers and used in diagnosis, along with the increased need for quantitative assessment of the degree of staining, number of cells, or spatial arrangement of cells within the tumor, has increased the volume and type of work that pathologists encounter in their diagnostic workflow. Our team works on the development of tools for quantitative digital pathology analysis that can benefit pathologists, by building and validating semi-automated algorithms for cellular quantification and intensity scoring of stained slides. We use machine learning methods to learn features that distinguish different morphological regions from pathologist annotations. These are then fed into a tissue segmentation and classification framework to break the tissue down into its components, either on the individual cell level, or the glandular level. Staining intensity is quantified following colour deconvolution of the individual stain components, and reporting metrics are designed, in close collaboration with pathologists and biological scientists, to identify the appropriate outputs for comparing between treatment groups or different cancer types.

The use of multiplexed digital pathology stains allows us to build a generalized analytical framework to perform “tissue cytometry”. This new technology can extract quantitative image-derived features in a reproducible and robust fashion, providing clinicians and biological scientists with tools to measure previously inaccessible phenomena, like measuring the hypoxic gradient directly within tumor sections, or comparing glucose uptake to lactic acid production in the same tumor sample. This approach establish the foundation for a bridge between traditional morphometric assessment of tumor biopsies, and the detailed spatially resolved chemical and molecular content maps of each tumor, providing an invaluable toolkit for the discovery of cancer molecular subtypes, and development of therapeutic interventions.

Biography: Dr. Trevor McKee received his Ph.D. in Biological Engineering from the Massachusetts Institute of Technology in 2005, in the laboratory of Dr. Rakesh Jain of Harvard Medical School. During his graduate work, he pioneered the application of new imaging and analysis technologies to studying drug transport within tumors, and on developing methods to improve drug delivery. He also holds a Bachelors of Science in Chemical Engineering with a Biotechnology minor from the University at Buffalo. He moved to Toronto to continue postdoctoral work at the Ontario Cancer Institute, applying multi-modality imaging and quantitative image analysis methods to study preclinical cancer models. He has a successful track record of high-impact publications with a number of clinical and basic science collaborators, and has also collaborated with pharmaceutical companies on imaging-based preclinical testing of new compounds. He is currently Image Analysis Core Manager of the STTARR Innovation Centre, and manages a team of analysts to develop new algorithms for machine-learning powered image segmentation and quantification across a number of disease sites. His research interests lie in studying the tumor microenvironment, drug and oxygen delivery, and the development of tools for “tissue cytometry” – deriving complex biological and spatial relationships from tissue sections via computational image analysis methods.

Abstract: The scale of data being generated in medicine and research can easily overwhelm typical analytic capabilities. This is particularly true with MRI/fMRI scanning, genomics data, streaming/wearables data in addition to other clinical data types, especially if in combination.

Challenges include 1) large file sizes often in heterogeneous formats 2) currently no standard Protocol exists for extraction of standardized characteristics, and 3) traditional methods for group-wise comparison can often result in spurious findings.

The talk will address these challenges by discussing customized processing pipelines built for multiple data types in biomedicine, which enable effective machine learning and other types of analytics on these datasets. This approach leverages the rapid model building capabilities of our real-time machine learning software to iterate through normalization parameters for each data type and disease class. In addition, this platform allows easy integration between the various medical data types (genome sequence, phenotypic, and metabolic data) allowing generation of more comprehensive disease classification models.

The ability to standardize and pre-process multiple types of biomedical data for machine learning, no matter the source and type, and effectively combine it with other data types is a powerful capability and holds promise for the future of diagnostics and precision medicine.

Biography: Shiva Amiri is the CEO of BioSymetrics Inc. where they are developing a unique real-time machine learning technology for the analysis of massive data in biomedicine. BioSymetrics specializes in providing optimized pipelines for complex data types and effective methods in the analytics of integrated data. Prior to BioSymetrics she was the Chief Product Officer at Real Time Data Solutions Inc., she has led the Informatics and Analytics team at the Ontario Brain Institute, where they developed Brain-CODE, a large-scale neuroinformatics platform across the province of Ontario. She was previously the head of the British High Commission’s Science and Innovation team in Canada. Shiva completed her Ph.D. in Computational Biochemistry at the University of Oxford and her undergraduate degree in Computer Science and Human Biology at the University of Toronto. Shiva is involved with several organisations including Let’s Talk Science and Shabeh Jomeh International.

Wednesday May 31, 2017 at 6:00 p.m. hear about the work of Dr. Sanja Fidler, Assistant Professor in Machine Learning and Computer Vision, University of Toronto and Dr. Inmar Givoni, Director of Machine Learning at Kindred Systems Inc., as part of “Women in Robotics: Building Smart Robots with AI”.

Get Your Bot On!, its partners Society of Women Engineers Toronto, IEEE Toronto Engineering in Medicine and Biology Society (EBMS) and IEEE Women in Engineering are pleased to bring you the ‘Women in Robotics Speaker Series’. This series celebrates the work of women in the field of robotics and provides a forum for them to share their work and career with the community. We invite all community members to come and learn, participate in the discussion, and celebrate the contribution of women to this field.

Dr. Sanja Fidler is an Assistant Professor at the Department of Computer Science, University of Toronto. She is the recipient of the Amazon Academic Research Award (2017) and the NVIDIA Pioneer of AI Award (2016). Previously she was a Research Assistant Professor at TTI-Chicago a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012.

In 2010 she visited UC Berkeley. She has served as a Program Chair of the 3DV conference, and as an Area Chair of CVPR, EMNLP, ICCV, ICLR, and NIPS. Together with Rich Zemel and Raquel Urtasun, she received the NVIDIA Pioneer of AI award.

Her main research interests are object detection, 3D scene understanding, and the intersection of language and vision.

Dr. Inmar Givoni is the Director of Machine Learning at Kindred, where her team develops algorithms for machine intelligence, at the intersection of robotics and AI. Prior to that, she was the VP of Big Data at Kobo, where she led her team in applying machine learning and big data techniques to drive e-commerce, customer satisfaction, CRM, and personalization in the e-pubs and e-readers business. She first joined Kobo in 2013 as a senior research scientist working on content analysis, website optimization, and reading modelling among other things. Prior to that, Inmar was a member of technical staff at Altera (now Intel) where she worked on optimization algorithms for cutting-edge programmable logic devices.

Inmar received her PhD (Computer Science) in 2011 from the University of Toronto, specializing in machine learning, and was a visiting scholar at the University of Cambridge. During her graduate studies, she worked at Microsoft Research, applying machine learning approaches for e-commerce optimization for Bing, and for pose-estimation in the Kinect gaming system. She holds a BSc in computer science and computational biology from the Hebrew University in Jerusalem. She is an inventor of several patents and has authored numerous top-tier academic publications in the areas of machine learning, computer vision, and computational biology. She is a regular speaker at big data, analytics, and machine learning events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths.

Friday May 26, 2017 at 1:30 p.m. Dr. Sergio A. A. Freitas, Associate Professor in the Gama Engineering College (FGA) and Director of the Distance Education Center at the University of Brasilia (UnB), Brazil, will be presenting “Designing a Gamification Course for an Higher Education Audience”.

Abstract: The gamification of activities in classrooms has become of great interest in higher education. Today’s students have a lot of experience in virtual environments and games, and researchers who have tested/used gamification in their classrooms have reported an increase in student engagement and retention.

At the end of the workshop it is expected that the participant will be able to design a basic gamified course.

Biography: Dr. Sergio A. A. Freitas is currently an Associate Professor in the Gama Engineering College (FGA) and Director of the Distance Education Center at the University of Brasilia (UnB), Brazil. He is also the coordinator of research in the FGA Software Factory Laboratory. His current research projects focus on interdisciplinary studies and applications of learning methodologies on engineering undergraduate courses, and software engineering methodologies. Prof. Freitas areas of expertise include gamification, PBL, virtual learning environments in education and training, and software engineering methodologies. Dr. Freitas has coauthored journal publications, conference articles and book chapters in the aforementioned topics, and has coordinated and participated on many projects from various funding agencies CNPq, FAP-ES, FAP-DF, Cebraspe, and Brazilian Federal Ministries.

Friday May 12, 2017 the School of Engineering Technology and Applied Science and the Centennial Energy Institute invite you to our 2017 E3 Symposium: The Future is Smart: The Transformation of Canadian Manufacturing. This event will bring together advanced manufacturing innovators from across a number of sectors in the economy. The event will feature industry titans sharing best practices.

The Internet of Things is a network of smart products, or “things”, that use embedded sensors, software, and electronics to communicate with each other over a network. The communication data can be analyzed by cloud based software to derive actionable information, leading to predictive and prescriptive outcomes.

Biography: Dr. Pooja Viswanathan is the Co-founder and CEO of Braze Mobility Inc. Dr. Viswanathan has a PhD in Robotics and Assistive Technology, is a Post-Doctoral Fellow at the University of Toronto and the AGE-WELL Network of Centres of Excellence, and is an Ontario Brain Institute Entrepreneur. Dr. Viswanathan is a passionate and accomplished innovator and still makes time for mentorship and education of the next generation of young innovators.

Biography: Farzad Rayegani is credited with developing an applied research program involving students, graduates and faculty mentors to address technological and educational needs of the Halton and Peel regions. Over the past 10 years, he has been simultaneously partnering with SME enterprises on product and process innovation projects while developing an applied research program involving students, graduates and faculty mentors to examine issues of product development / refinement, process automation, systems integration and manufacturing management. In the past year, this work has been bolstered by a range of successful, high-profile, federally funded projects with companies in both regions.

Under his leadership, through the Centre for Advanced Manufacturing and Design Technologies (CAMDT), Sheridan has been reaching out to a significant number of manufacturers in Brampton, Mississauga and Oakville, particularly small and medium enterprises, to support adoption and integration of efficient manufacturing practices and product innovation performance and improvements. CAMDT now supports over a dozen local and regional SMEs who are struggling with limited availability of technological, human, financial, and management resources.

Under his leadership, Sheridan College recently become a member of the CDIO Initiative – a worldwide movement to restore the balance between teaching practice skills and the fundamentals of math and science to engineering students. What started as a partnership between MIT and a few Swedish universities in 2001 has gained significant international momentum, with 103 institutions adopting the model. Sheridan is the fifth Canadian institution and the first college in the world to be accepted.

As a CDIO collaborator, Farzad is seeking to develop a new curriculum structure based on a new philosophy for engineering education. The framework educates students to Conceive, Design, Implement and Operate complex, value-added engineering products, processes and systems in a modern, team-based, global environment. He aims to develop a curriculum rich in project-based, hands-on learning, producing engineers who are “ready to engineer” when they graduate.

Farzad is ASME chair on additive manufacturing. As the committee chair, he will be leading the launch of ASME’s inaugural additive manufacturing challenge designed to give mechanical and multi-disciplinary undergraduate students around the world an opportunity to re-engineer existing products or create new designs that minimize energy consumption and/or improve energy efficiency. As chair, he will also be collaborating with ME department heads to develop educational material on behalf of ASME to benefit the educators and students.

Farzad was recently designated an Engineers Canada Fellow by Engineers Canada. This prestigious award is presented in recognition of exceptional contributions to the engineering profession in Canada.

Farzad has been a full-time professor in Sheridan’s Faculty of Applied Science and Technology since 2004. Currently, he is the associate dean of the School of Mechanical and Electrical Engineering & Technology and director of the Centre for Advanced Manufacturing and Design Technologies (CAMDT).

Abstract: Software is taking the planet by storm. Whether is engineering, manufacturing, medicine, business, arts, or education, the use of software is changing the way we live and is helping to improve people’s lives.

In this talk we will present several emerging trends in software, computing, and application development, as well as show some of the recent applications in various areas. Most importantly, we will relate the recent changes to ongoing curriculum updates to computing program across the education system.

Biography: Ilia has a Ph.D. in Applied mathematics, and more than 30 years of experience in mathematical modeling, software development, teaching, applied research, and curriculum development.

His main areas of expertise include mathematical modeling, Java and .NET programming, and mobile application development. Ilia has developed several automated systems for signal processing of geophysical data including the solution of inverse resistivity problem in resistivity logging. He is very interested in applications of machine learning in both engineering and education and has developed an application for predicting student retention in community colleges using institutional data and ensemble learning. Ilia has developed and taught courses in Software Systems Design and Computer Communications & Networking degree programs, as well as courses in Software Engineering Technology programs. Ilia has been principal investigator and/or co-investigator in several ARIC projects. He is also an Information Technology Management and Continuing Education part-time instructor, at Ryerson University (2007 – Present). Currently he is teaching Emerging Technologies course for Software Engineering Technology students, Centennial College.

Abstract: Cyber Security is one of the hottest technology topics ensuring the safety and reliability of the Electrical Grid against cyber-attacks from hackers. This seminar will be a great opportunity for students, new grads, and engineers to have a general overview on cyber security issues and challenges for utilities in North America. Industry Standards such as NERC CIP will be discussed, as will career opportunities on this field.

Join us on our first seminar on Cyber Security with IEEE Toronto Section. We look forward to seeing you at the event!

Doug Westlund, P. Eng., has 30 years’ experience in technology and cyber security in the utility and telecommunications markets. In his role at AESI he assists utility executive teams and their Boards with strategic planning and risk management. He has led more than 100 cyber security projects for generation, transmission and distribution utilities, developed risk management for the Ontario LDC insurer (MEARIE), and developed cyber security best practices and programs for the American Public Power Association and its 2,000 distribution utility members.